Neural Activity in Macaque Parietal Cortex Reflects Temporal Integration of Visual Motion Signals during Perceptual Decision Making

Perceptual decision making is often modeled as perfect integration of sequential sensory samples until the accumulated total reaches a fixed decision bound. In that view, the buildup of neural activity during perceptual decision making is attributed to temporal integration. However, an alternative explanation is that sensory estimates are computed quickly with a low-pass filter and combined with a growing signal reflecting the urgency to respond and it is the latter that is primarily responsible for neural activity buildup. These models are difficult to distinguish empirically because they make similar predictions for tasks in which sensory information is constant within a trial, as in most previous studies. Here we presented subjects with a variant of the classic constant-coherence motion discrimination (CMD) task in which we inserted brief motion pulses. We examined the effect of these pulses on reaction times (RTs) in two conditions: 1) when the CMD trials were blocked and subjects responded quickly and 2) when the same CMD trials were interleaved among trials of a variable-motion coherence task that motivated slower decisions. In the blocked condition, early pulses had a strong effect on RTs but late pulses did not, consistent with both models. However, when subjects slowed their decision policy in the interleaved condition, later pulses now became effective while early pulses lost their efficacy. This last result contradicts models based on perfect integration of sensory evidence and implies that motion signals are processed with a strong leak, equivalent to a low-pass filter with a short time constant.

Download Full-text

Transient neuronal suppression for exploitation of new sensory evidence

Nature Communications ◽

10.1038/s41467-021-27697-4 ◽

2022 ◽

Vol 13 (1) ◽

Author(s):

Maxwell Shinn ◽

Daeyeol Lee ◽

John D. Murray ◽

Hyojung Seo

Keyword(s):

Decision Making ◽

Neural Activity ◽

Temporal Integration ◽

Motor Preparation ◽

Stimulus Onset ◽

Frontal Eye Field ◽

Perceptual Decision Making ◽

Behavioral Studies ◽

The Face ◽

Sensory Evidence

AbstractIn noisy but stationary environments, decisions should be based on the temporal integration of sequentially sampled evidence. This strategy has been supported by many behavioral studies and is qualitatively consistent with neural activity in multiple brain areas. By contrast, decision-making in the face of non-stationary sensory evidence remains poorly understood. Here, we trained monkeys to identify and respond via saccade to the dominant color of a dynamically refreshed bicolor patch that becomes informative after a variable delay. Animals’ behavioral responses were briefly suppressed after evidence changes, and many neurons in the frontal eye field displayed a corresponding dip in activity at this time, similar to that frequently observed after stimulus onset but sensitive to stimulus strength. Generalized drift-diffusion models revealed consistency of behavior and neural activity with brief suppression of motor output, but not with pausing or resetting of evidence accumulation. These results suggest that momentary arrest of motor preparation is important for dynamic perceptual decision making.

Download Full-text

Population-wide distributions of neural activity during perceptual decision-making

Progress in Neurobiology ◽

10.1016/j.pneurobio.2012.09.004 ◽

2013 ◽

Vol 103 ◽

pp. 156-193 ◽

Cited By ~ 35

Author(s):

Adrien Wohrer ◽

Mark D. Humphries ◽

Christian K. Machens

Keyword(s):

Decision Making ◽

Neural Activity ◽

Perceptual Decision Making ◽

Perceptual Decision

Download Full-text

Slow drift of neural activity as a signature of impulsivity in macaque visual and prefrontal cortex

10.1101/2020.01.10.902403 ◽

2020 ◽

Cited By ~ 2

Author(s):

Benjamin R. Cowley ◽

Adam C. Snyder ◽

Katerina Acar ◽

Ryan C. Williamson ◽

Byron M. Yu ◽

...

Keyword(s):

Decision Making ◽

Prefrontal Cortex ◽

Neural Activity ◽

Internal State ◽

Sensory Stimulus ◽

Perceptual Decision Making ◽

Population Activity ◽

Perceptual Decision ◽

Slow Drift ◽

Sensory Evidence

AbstractAn animal’s decision depends not only on incoming sensory evidence but also on its fluctuating internal state. This internal state is a product of cognitive factors, such as fatigue, motivation, and arousal, but it is unclear how these factors influence the neural processes that encode the sensory stimulus and form a decision. We discovered that, over the timescale of tens of minutes during a perceptual decision-making task, animals slowly shifted their likelihood of reporting stimulus changes. They did this unprompted by task conditions. We recorded neural population activity from visual area V4 as well as prefrontal cortex, and found that the activity of both areas slowly drifted together with the behavioral fluctuations. We reasoned that such slow fluctuations in behavior could either be due to slow changes in how the sensory stimulus is processed or due to a process that acts independently of sensory processing. By analyzing the recorded activity in conjunction with models of perceptual decision-making, we found evidence for the slow drift in neural activity acting as an impulsivity signal, overriding sensory evidence to dictate the final decision. Overall, this work uncovers an internal state embedded in the population activity across multiple brain areas, hidden from typical trial-averaged analyses and revealed only when considering the passage of time within each experimental session. Knowledge of this cognitive factor was critical in elucidating how sensory signals and the internal state together contribute to the decision-making process.

Download Full-text

The Functional Anatomy of a Perceptual Decision in the Human Brain

Journal of Neurophysiology ◽

10.1152/jn.00364.2009 ◽

2010 ◽

Vol 103 (3) ◽

pp. 1179-1194 ◽

Cited By ~ 76

Author(s):

Andrew S. Kayser ◽

Bradley R. Buchsbaum ◽

Drew T. Erickson ◽

Mark D'Esposito

Keyword(s):

Decision Making ◽

Visual Motion ◽

Functional Anatomy ◽

Sensory Information ◽

Imaging Study ◽

Neural Circuitry ◽

Perceptual Decision Making ◽

Visuomotor Integration ◽

Perceptual Decision ◽

Accumulator Models

Our ability to make rapid decisions based on sensory information belies the complexity of the underlying computations. Recently, “accumulator” models of decision making have been shown to explain the activity of parietal neurons as macaques make judgments concerning visual motion. Unraveling the operation of a decision-making circuit, however, involves understanding both the responses of individual components in the neural circuitry and the relationships between them. In this functional magnetic resonance imaging study of the decision process in humans, we demonstrate that an accumulator model predicts responses to visual motion in the intraparietal sulcus (IPS). Significantly, the metrics used to define responses within the IPS also reveal distinct but interacting nodes in a circuit, including early sensory detectors in visual cortex, the visuomotor integration system of the IPS, and centers of cognitive control in the prefrontal cortex, all of which collectively define a perceptual decision-making network.

Download Full-text

Neural correlates and neural computations in posterior parietal cortex during perceptual decision-making

Frontiers in Integrative Neuroscience ◽

10.3389/fnint.2012.00086 ◽

2012 ◽

Vol 6 ◽

Cited By ~ 11

Author(s):

Alexander C. Huk ◽

Miriam L. R. Meister

Keyword(s):

Decision Making ◽

Parietal Cortex ◽

Posterior Parietal Cortex ◽

Neural Correlates ◽

Perceptual Decision Making ◽

Perceptual Decision ◽

Neural Computations ◽

Posterior Parietal

Download Full-text

Causal contributions of parietal cortex to perceptual decision-making during stimulus categorization

Nature Neuroscience ◽

10.1038/s41593-019-0383-6 ◽

2019 ◽

Vol 22 (6) ◽

pp. 963-973 ◽

Cited By ~ 13

Author(s):

Lin Zhong ◽

Yuan Zhang ◽

Chunyu A. Duan ◽

Ji Deng ◽

Jingwei Pan ◽

...

Keyword(s):

Decision Making ◽

Parietal Cortex ◽

Perceptual Decision Making ◽

Perceptual Decision

Download Full-text

Transient neuronal suppression for exploitation of new sensory evidence

10.1101/2020.11.29.403089 ◽

2020 ◽

Author(s):

Maxwell Shinn ◽

Daeyeol Lee ◽

John D. Murray ◽

Hyojung Seo

Keyword(s):

Decision Making ◽

Neural Activity ◽

Temporal Integration ◽

Motor Preparation ◽

Stimulus Onset ◽

Frontal Eye Field ◽

Perceptual Decision Making ◽

Behavioral Studies ◽

The Face ◽

Sensory Evidence

AbstractIn noisy but stationary environments, decisions should be based on the temporal integration of sequentially sampled evidence. This strategy has been supported by many behavioral studies and is qualitatively consistent with neural activity in multiple brain areas. By contrast, decision-making in the face of non-stationary sensory evidence remains poorly understood. Here, we trained monkeys to identify the dominant color of a dynamically refreshed bicolor patch that becomes informative after a variable delay. Animals' behavioral responses were briefly suppressed after evidence changes, and many neurons in the frontal eye field displayed a corresponding dip in activity at this time, similar to that frequently observed after stimulus onset. Generalized drift-diffusion models revealed consistency of behavior and neural activity with brief suppression of motor output, but not with pausing or resetting of evidence accumulation. These results suggest that momentary arrest of motor preparation is an important component of dynamic perceptual decision making.

Download Full-text

Behavioural and neural indices of perceptual decision-making in autistic children during visual motion tasks

10.31234/osf.io/s5r3m ◽

2021 ◽

Author(s):

Catherine Manning ◽

Cameron Dale Hassall ◽

Laurence Hunt ◽

Anthony Norcia ◽

Eric-Jan Wagenmakers ◽

...

Keyword(s):

Decision Making ◽

Visual Motion ◽

Sensory Information ◽

Decision Time ◽

Motion Processing ◽

Autistic Children ◽

Perceptual Decision Making ◽

Perceptual Decision ◽

Diffusion Modelling ◽

Evidence Accumulation

Many studies report atypical responses to sensory information in autistic individuals, yet it is not clear which stages of processing are affected, with little consideration given to decision-making processes. We combined diffusion modelling with high-density EEG to identify which processing stages differ between 50 autistic and 50 typically developing children aged 6-14 years during two visual motion tasks. Our pre-registered hypotheses were that autistic children would show task-dependent differences in sensory evidence accumulation, alongside a more cautious decision-making style and longer non-decision time across tasks. We tested these hypotheses using hierarchical Bayesian diffusion models with a rigorous blind modelling approach, finding no conclusive evidence for our hypotheses. Using a data-driven method, we identified a response-locked centro-parietal component previously linked to the decision-making process. The build-up in this component did not consistently relate to evidence accumulation in autistic children. This suggests that the relationship between the EEG measure and diffusion-modelling is not straightforward in autistic children. Compared to a related study of children with dyslexia, motion processing differences appear less pronounced in autistic children. Our results also provide weak evidence that ADHD symptoms moderate perceptual decision-making in autistic children.

Download Full-text

Time-Varying Perturbations Can Distinguish Among Integrate-to-Threshold Models for Perceptual Decision Making in Reaction Time Tasks

Neural Computation ◽

10.1162/neco.2009.07-08-817 ◽

2009 ◽

Vol 21 (8) ◽

pp. 2336-2362 ◽

Cited By ~ 9

Author(s):

Xiang Zhou ◽

KongFatt Wong-Lin ◽

Holmes Philip

Keyword(s):

Decision Making ◽

Linear Models ◽

Temporal Integration ◽

High Signal ◽

Threshold Models ◽

Time Varying ◽

Perceptual Decision Making ◽

Behavioral Experiments ◽

Perceptual Decision ◽

Standard Deviations

Several integrate-to-threshold models with differing temporal integration mechanisms have been proposed to describe the accumulation of sensory evidence to a prescribed level prior to motor response in perceptual decision-making tasks. An experiment and simulation studies have shown that the introduction of time-varying perturbations during integration may distinguish among some of these models. Here, we present computer simulations and mathematical proofs that provide more rigorous comparisons among one-dimensional stochastic differential equation models. Using two perturbation protocols and focusing on the resulting changes in the means and standard deviations of decision times, we show that for high signal-to-noise ratios, drift-diffusion models with constant and time-varying drift rates can be distinguished from Ornstein-Uhlenbeck processes, but not necessarily from each other. The protocols can also distinguish stable from unstable Ornstein-Uhlenbeck processes, and we show that a nonlinear integrator can be distinguished from these linear models by changes in standard deviations. The protocols can be implemented in behavioral experiments.

Download Full-text